Distributed partition detection and recovery using UAV in wireless sensor and actor networks

Wireless Sensor and Actor Networks (WSANs) have been extensively employed in various domains ranging from elementary data collection to real-time control and monitoring for critical applications. Network connectivity is a vital robustness measure for overall network performance. Different network functions such as routing, scheduling, and QoS provisioning depends on network connectivity. The failure of articulation points in the network disassociates the network into disjoint segments. We proposed Distributed Partition Detection and Recovery using Unmanned Aerial Vehicle (UAV) (DPDRU) algorithm, as an optimal solution to recover the partitioned network. It consists of three steps: Initialization, Operational and Detection, and Recovery. In the Initialization phase sink node collects all the information about the network. In the Operational and Detection phase, network nodes communicate regularly by exchanging HEARTBEATS, detects failure if some nodes do not get a message from the neighbor node and send failure reports, and sink node identifies network partition. In the recovery phase, the sink node sends UAV at the positional coordinates of the failed node and examines network recovery after UAV reaches the desired location. Our approach primarily focuses on reducing message overhead by sending few update messages to sink node and energy consumption by engaging network nodes only for communication. The requirements of the recovery process (physical movement and communication) are fulfilled by UAV. The algorithm is tested according to the following parameters: Detection Time, Recovery Time, message overhead, and distance traveled by UAV. Simulation results validate the efficacy of the proposed algorithm based on these parameters to provide reliable results. The minimum and the maximum number of messages transmitted are 11 for 10 nodes and 24 for 100 nodes respectively. Hence these results demonstrate that the message overhead in our proposed solution is less as compared to other techniques when the number of nodes increases.

An Efficient and Stable Routing Algorithm in Mobile Ad Hoc Network

Mobile Ad hoc Network (MANET) is mainly designed to set up communication among devices in infrastructure-less wireless communication network. Routing in this kind of communication network is highly affected by its restricted characteristics such as frequent topological changes and limited battery power. Several research works have been carried out to improve routing performance in MANET. However, the overall performance enhancement in terms of packet delivery, delay and control message overhead is still not come into the wrapping up. In order to overcome the addressed issues, an Efficient and Stable-AODV (EFST-AODV) routing scheme has been proposed which is an improvement over AODV to establish a better quality route between source and destination. In this method, we have modified the route request and route reply phase. During the route request phase, cost metric of a route is calculated on the basis of parameters such as residual energy, delay and distance. In a route reply phase, average residual energy and average delay of overall path is calculated and the data forwarding decision is taken at the source node accordingly. Simulation outcomes reveal that the proposed approach gives better results in terms of packet delivery ratio, delay, throughput, normalized routing load and control message overhead as compared to AODV.

A Data Driven Trust Mechanism Based on Blockchain in IoT Sensor Networks for Detection and Mitigation of Attacks

Utilization of smart applications in various domains is facilitated pervasively by sensor nodes (SN) that are connected in a wireless manner and a number of smart things. Hazards due to internal and external attacks exist along with the advantages of the smart things and its applications. Security measures are influenced by three main factors namely scalability, latency and network lifespan, without which mitigation of internal attacks is a challenge. The deployment of SN based Internet of things (IoT) is decentralized in nature. However, centralized solutions and security measures are provided by most researchers. A data driven trust mechanism based on blockchain is presented in this paper as a decentralized and energy efficient solution for detection of internal attacks in IoT powered SNs. In grey and black hole attack settings, the message overhead is improved using the proposed model when compared to the existing solutions. In both grey and black hole attacks, the time taken for detection of malicious nodes is also reduced considerably. The network lifetime is improved significantly due to the enhancement of these factors.

A Blockchain-Based Multi-Mobile Code-Driven Trust Mechanism for Detecting Internal Attacks in Internet of Things

A multitude of smart things and wirelessly connected Sensor Nodes (SNs) have pervasively facilitated the use of smart applications in every domain of life. Along with the bounties of smart things and applications, there are hazards of external and internal attacks. Unfortunately, mitigating internal attacks is quite challenging, where network lifespan (w.r.t. energy consumption at node level), latency, and scalability are the three main factors that influence the efficacy of security measures. Furthermore, most of the security measures provide centralized solutions, ignoring the decentralized nature of SN-powered Internet of Things (IoT) deployments. This paper presents an energy-efficient decentralized trust mechanism using a blockchain-based multi-mobile code-driven solution for detecting internal attacks in sensor node-powered IoT. The results validate the better performance of the proposed solution over existing solutions with 43.94% and 2.67% less message overhead in blackhole and greyhole attack scenarios, respectively. Similarly, the malicious node detection time is reduced by 20.35% and 11.35% in both blackhole and greyhole attacks. Both of these factors play a vital role in improving network lifetime.

SARL: A reinforcement learning based QoS-aware IoT service discovery model

The IoT environment includes the enormous amount of atomic services with dynamic QoS compared with traditional web services. In such an environment, in the service composition process, discovering a requested service meeting the required QoS is a di cult task. In this work, to address this issue, we propose a peer-to-peer-based service discovery model, which looks for the information about services meeting the requested QoS and functionality on an overlay constructed with users of services versus service nodes, with probably constrained resources. However, employing a plain discovery algorithm on the overlay network such as flooding, or k-random walk could cause high message overhead or delay. This necessitates an intelligent and adaptive discovery algorithm, which adapts itself based on users’ previous queries and the results. To fill this gap, the proposed service discovery approach is equipped with a reinforcement learning-based algorithm, named SARL. The reinforcement learning-based algorithm enables SARL to significantly reduce delay and message overhead in the service discovery process by ranking neighboring nodes based on users’ service request preferences and the service query results. The proposed model is implemented on the OMNet simulation platform. The simulation results demonstrate that SARL remarkably outperforms the existing approaches in terms of message overhead, reliability, timeliness, and energy usage efficiency.

A Feasibility Analysis of an Application-Based Partial Initialization (API) Protocol for Underwater Wireless Acoustic Sensor Networks

Initialization methods for underwater wireless acoustic sensor networks (UWASNs) have been proposed as a subset of other network protocols under the simple assumption that all the nodes in the network can be initialized at once. However, it is generally time- and energy-intensive to initialize all nodes in a UWASN due to unstable underwater channel conditions. To improve network efficiency, we propose the Application-based Partial Initialization (API) protocol, which initializes only the same number of nodes as the number of activated nodes required to run a specific application. Reducing the number of active nodes is also particularly advantageous underwater since the replacement of batteries is costly. To the best of our knowledge, the API is the first approach that initializes nodes partially according to applications. Thus, we investigate the feasibility of the API for a UWASN by analyzing its performance via simulations. From the results, it is shown that the API provides similar data statistics compared with the conventional full initialization that initializes all nodes. Moreover, the API outperforms the full initialization in terms of the initialization time and message overhead performances.

Distributed Region-Based Monitoring in Low-Power Listening Wireless Sensor Networks

Advancement in IoT technology and the concept of Information-Centric Networking lead to less importance of node individuality since several nodes can work interchangeably. Multiple sensor nodes can be grouped into a region and monitored as one instance to guarantee sufficient coverage over the region. Therefore, a single node fault often does not need to be reported unless it is the last node in the region. In addition, there are occasions where a central monitor station cannot rely on continuous data delivery from nodes or regions to decide whether they are still alive, such as situations when nodes are deployed to detect rare events. Moreover, low-power listening MAC protocols, which significantly help reducing power consumption while nodes are mostly idle, put a lot more work on the transmission process. In such situations it is desirable to minimize status reports to the central monitor station. A distributed region-based monitoring scheme, or DRMON, is then proposed to facilitate this circumstance. This approach designates a representative to each region so that it can be used as an indicator of the region's status with a mechanism to re-elect a new representative until all nodes in the respective region are dead, implying region inactiveness. We evaluate the suitability of DRMON over various scenarios in two aspects: centralized vs. distributed monitoring schemes and individual-based vs. region-based monitoring schemes. Simulation results indicate that region-based schemes outperform the individual schemes in terms of power consumption and scalability when the number of regions is low. The distributed schemes also yield better efficiency in terms of message overhead and load distribution. In addition, detection accuracy of all schemes is not significantly different and fault detection delay is guaranteed. This outcome suggests that in the case where existence of individual node is out of concern, distributed region-based fault monitoring scheme could be employed to reduce energy usage and lower message overhead while retaining the detection accuracy.

T0RTT: Non-Interactive Immediate Forward-Secret Single-Pass Circuit Construction

Maintaining privacy on the Internet with the presence of powerful adversaries such as nation-state attackers is a challenging topic, and the Tor project is currently the most important tool to protect against this threat. The circuit construction protocol (CCP) negotiates cryptographic keys for Tor circuits, which overlay TCP/IP by routing Tor cells over n onion routers. The current circuit construction protocol provides strong security guarantees such as forward secrecy by exchanging 𝒪(n2) messages.For several years it has been an open question if the same strong security guarantees could be achieved with less message overhead, which is desirable because of the inherent latency in overlay networks. Several publications described CCPs which require only 𝒪(n) message exchanges, but significantly reduce the security of the resulting Tor circuit. It was even conjectured that it is impossible to achieve both message complexity 𝒪(n) and forward secrecy immediately after circuit construction (so-called immediate forward secrecy). Inspired by the latest advancements in zero round-trip time key exchange (0-RTT), we present a new CCP protocol Tor 0-RTT (T0RTT). Using modern cryptographic primitives such as puncturable encryption allow to achieve immediate forward secrecy using only 𝒪(n) messages. We implemented these new primitives to give a first indication of possible problems and how to overcome them in order to build practical CCPs with 𝒪(n) messages and immediate forward secrecy in the future.

A Backbone Formation Protocol Using Minimum Spanning Tree in Cognitive Radio Networks

Numerous research articles exist for backbone formation in wireless networks; however, they cannot be applied straightforward in cognitive radio networks (CRN) due to its peculiar characteristics. Since virtual backbone has many advantages such as reduced routing overhead, dynamic maintenance, and fast convergence speed, the authors propose a backbone formation protocol in CRN. In this chapter, a backbone formation protocol is proposed using the concept of minimum spanning tree. The protocol is based on non-iterative approach, thus leading towards limited message overhead. The proposed algorithm first forms the minimum spanning tree, and second, the nodes having more than one neighbor are connected together to form the backbone.